A novel hybrid swarm optimized multilayer neural network for spatial prediction of flash floods in tropical areas using sentinel-1 SAR imagery and geospatial data

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg–Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Pharmacogenomic Analysis of CYP3A5*3 and Tacrolimus Trough Concentrations in Vietnamese Renal Transplant Outcomes

Thi Van Anh Nguyen,1,&ast; Ba Hai Le,2,&ast; Minh Thanh Nguyen,2,&ast; Viet Thang Le,3,&ast; Viet Tien Tran,4,&ast; Dinh Tuan Le,5,&ast; Duong Anh Minh Vu,2,&ast; Quy Kien Truong,3,&ast; Trong Hieu Le,2,&ast; Huong Thi Lien Nguyen2,&ast; 1Department of Pharmacy, 103 Military Hospital, Hanoi, Vietnam; 2Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam; 3Department of Nephrology and Dialysis, 103 Military Hospital, Hanoi, Vietnam; 4Department of Infectious Diseases, 103 Military Hospital, Hanoi, Vietnam; 5Department of Rheumatology and Endocrinology, 103 Military Hospital, Hanoi, Vietnam&ast;These authors contributed equally to this workCorrespondence: Huong Thi Lien Nguyen, Department of Clinical Pharmacy, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi, Vietnam, Tel +84904308406, Email [email protected]: CYP3A5 polymorphisms have been associated with variations in the pharmacokinetics of tacrolimus (Tac) in kidney transplant patients. Our study aims to quantify how the CYP3A5 genotype influences tacrolimus trough concentrations (C0) in a Vietnamese outpatient population by selecting an appropriate population pharmacokinetic model of Tac for our patients.Patients and Methods: The external dataset was obtained prospectively from 54 data of adult kidney transplant recipients treated at the 103 Military Hospital. All published Tac population pharmacokinetic models were systematically screened from PubMed and Scopus databases and were selected based on our patient’s available characteristics. Mean absolute prediction error (MAPE), mean prediction error, and goodness-of-fit plots were used to identify the appropriate model for finding the formula that identifies the influence of CYP3A5 genotype on the pharmacokinetic data of Vietnamese patients.Results: The model of Zhu et al had a good predictive ability with MAPE of 19.29%. The influence of CYP3A5 genotype on tacrolimus clearance was expressed by the following formulas: . The simulation result showed that Tac C0 was significantly higher in patients not expressing CYP3A5 (p< 0.001).Conclusion: The incorporation of the CYP3A5 phenotype into Zhu’s structural model has significantly enhanced our ability to predict Tacrolimus trough levels in the Vietnamese population. This study’s results underscore the valuable role of CYP3A5 phenotype in optimizing the forecast of Tac concentrations, offering a promising avenue to assist health-care practitioners in their clinical decision-making and ultimately advance patient care outcomes.Keywords: tacrolimus, population pharmacokinetic, CYP3A5, Vietna

Enhancing Electron Transfer and Stability of Screen-Printed Carbon Electrodes Modified with AgNP-Reduced Graphene Oxide Nanocomposite

This paper presents a reliable solution to enhance the electron transfer and stability of screen-printed carbon electrodes (SPCEs) for the direct detection of pathogenic bacteria. A nanocomposite of silver nanoparticles (AgNPs) and reduced graphene oxide (rGO) was used to modify the SPCEs. Herein, the nanocomposite was synthesized via a hydrothermal method and then characterized by physicochemical methods. The electron transfer rate and electrochemical properties of the AgNP-rGO nanocomposite-modified SPCEs were investigated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy. Measurements were performed for the detection of Salmonella bacteria without any labels. Results showed that the nanocomposite firmly adhered to the surfaces of the SPCEs, led to an increase of approximately 160% in the peak current, and decreased the charge transfer resistance to 0.45 kΩ. Electrochemical stability was found in 30 CV cycles. The modified SPCEs could detect Salmonella bacteria directly at concentrations of 10–105 CFU/mL, with a limit of detection (LoD) of as low as 22 CFU/mL. A possible mechanism was proposed to explain the enhanced electron transfer on the surface and the stability of the AgNP-rGO nanocomposite-modified SPCEs. The biosensor showed high stability, cost-effectiveness, and simplicity for the direct detection of pathogenic bacteria. Graphical Abstract: [Figure not available: see fulltext.